diff options
Diffstat (limited to 'tests/validation/fixtures/ConvolutionLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/ConvolutionLayerFixture.h | 17 |
1 files changed, 3 insertions, 14 deletions
diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h index 6a100acef3..3d073e3f79 100644 --- a/tests/validation/fixtures/ConvolutionLayerFixture.h +++ b/tests/validation/fixtures/ConvolutionLayerFixture.h @@ -100,6 +100,8 @@ protected: TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, bool reshape_weights, const Size2D &dilation) { + const bool is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && _data_type == DataType::F32; + WeightsInfo weights_info(!reshape_weights, weights_shape.x(), weights_shape.y(), weights_shape[3]); TensorShape reshaped_weights_shape(weights_shape); @@ -107,12 +109,6 @@ protected: { // Check if its a "fully connected" convolution const bool is_fully_connected_convolution = (output_shape.x() == 1 && output_shape.y() == 1); - bool is_optimised = false; -#if defined(__arm__) - is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU == CPUTarget::ARMV7 && _data_type == DataType::F32; -#elif defined(__aarch64__) - is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV8 && _data_type == DataType::F32; -#endif /* defined(__arm__) || defined(__aarch64__) */ reshaped_weights_shape.collapse(3); @@ -167,14 +163,7 @@ protected: if(!reshape_weights) { - const bool is_fully_connected_convolution = (output_shape.x() == 1 && output_shape.y() == 1); - bool is_optimised = false; -#if defined(__arm__) - is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU == CPUTarget::ARMV7 && _data_type == DataType::F32; -#elif defined(__aarch64__) - is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV8 && _data_type == DataType::F32; -#endif /* defined(__arm__) || defined(__aarch64__) */ - + const bool is_fully_connected_convolution = (output_shape.x() == 1 && output_shape.y() == 1); TensorShape tmp_weights_shape(weights_shape); SimpleTensor<T> tmp_weights(tmp_weights_shape, _data_type, 1, _fractional_bits, _quantization_info); |